The invention relates to identifying and distinguishing observed objects by analyzing the image with a plurality of independent data inputs.
In E. Steinberg, P. Bigioli, and I. Raducan, U.S. Pat. No. 6,904,168, Oct. 22, 2001, “Workflow system for detection and classification of images suspected as pornographic,” the application involved detection and classification of images being suspected as being pornographic. This method employed shape, texture, curvature and pose characteristics of the images to rank certain pictures as high probability of being pornographic.
In D. A. Goldberg, U.S. Pat. No. 6,526,158, Feb. 25, 2003, “Method and system for obtaining person-specific images in a public venue,” facial recognition systems were used to find a specific person in an audience. A face recognition system was employed as well as other meta-information about that person.
In H. Nobuta, Y. Ueno, S. Matsuzaki, T. Toyama, M. Nakao, and N. Sugawara, U.S. Pat. No. 6,775,033, Aug. 10, 2004, “Image communication apparatus and communication control method thereof,” an image communication apparatus and control method of sending and receiving pictures was discussed.
In D. Lu, C. T. Shagrin, W. L. Thomas, M. Lee, B. Bernard, and J. Zhang, U.S. Pat. No. 5,550,928, Aug. 27, 1996, “Audience measurement system and method,” the goal was to find a particular member in the audience. A template matching scheme was presented, but it differs from the methodology presented in this patent application.
In S. M. Hoffberg, and L. I. Hoffberg-Borghesani, U.S. Pat. No. 5,774,357, Jun. 6, 1998, “Human-factored interface incorporating adaptive pattern recognition based controller apparatus,” an adaptive pattern recognition scheme was presented which used both temporal and spatial user characteristics, but differs from the material presented in the sequel in this patent application.
In D. A. Goldberg, M. B. Goldberg, M. D. Goldberg and B. M. Goldberg, U.S. Pat. No. 6,819,783, Nov. 14, 2003, “Obtaining person-specific images in a public venue,” disclosed a method and system for identifying images of people in a public venue by electronically merging identification information into the image information. This procedure provides a “tag” to identify the image with a marker to keep track of the person of interest.
In R. D. Sorkin and H. Dai, “Signal Detection Analysis of the Ideal Group,” Organizational Behavior and Human Decision Processes, 60, 1994, pp. 1-13 signal detection theory was used with analysis of the ideal group. It showed that the signal to noise ratio of certain key variables increased with the square root of the number of the constituent voters provided they were independent. An efficiency measure of performance of the observed group to decision making was identified.
In R. D. Sorkin, R. West, and D. E. Robinson, “Group Performance Depends on the Majority Rule,” Psychological Science, Vol. 9, No. 6, November, 1998, pp. 456-463, the majority rule was investigated when it may not be a simple majority in the decision process (for example two-thirds or three-fourths of the majority).
In R. D. Sorkin, C. J. Hays, and R. West, “Signal-Detection Analysis of Group Decision Making,” Psychological Review, Vol. 108, No. 1, 2001, pp. 183-203, signal detection theory was employed for groups of decision makers to examine their efficacy. As the group size changed, how this modified decision-making ability was studied.
Performance is examined in R. D. Sorkin, S. Luan, and J. Itzkowitz, “Group Decision and Deliberation: A Distributed Detection Process,” Book Chapter, Chapter 23, pp. 464-484, for a distributed framework for group decision where deliberation was performed. Investigation of the bias (used in the individual decision rules of each voter) was determined and its relationship to the likelihood ratios of the binary choices.
All references made in the present specification are herein incorporated by reference.